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I-Structures: Data structures for parallel computing

  • Arvind
  • Rishiyur S. Nikhil
  • Keshav K. Pingali
Arrays
Part of the Lecture Notes in Computer Science book series (LNCS, volume 279)

Abstract

It is difficult simultaneously to achieve elegance, efficiency and parallelism in functional programs that manipulate large data structures. We demonstrate this through careful analysis of program examples using three common functional data-structuring approaches—lists using Cons and arrays using Update (both fine-grained operators), and arrays using make-array (a “bulk” operator). We then present I-structures as an alternative, defining precisely the parallel operational semantics of Id, a language with I-structures. We show elegant, efficient and parallel solutions for the program examples in Id. I-structures make the language non-functional, but do not raise determinacy issues. Finally, we show that even in the context of purely functional languages, I-structures are invaluable for implementing functional data abstractions.

Keywords

Operational Semantic Functional Language Loop Body Dataflow Graph List Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • Arvind
    • 1
  • Rishiyur S. Nikhil
    • 1
  • Keshav K. Pingali
    • 2
  1. 1.MIT Lab. for Computer ScienceCambridgeUSA
  2. 2.Dept. of Computer Science, 303A Upson HallCornell UniversityIthacaUSA

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